Senior Data Engineer, AWS

Position Summary
We are seeking a Senior or Principal Data Engineer to design, build, and optimize data platforms on Amazon Web Services. This is a hands-on, AWS-native engineering role for someone who lives in the details of large-scale analytical data: tuning Redshift and Athena, writing production Python, and squeezing performance out of queries that run against multi-terabyte datasets. You'll own the architecture and reliability of data pipelines end to end, set the standard for engineering quality, and mentor others on what great looks like in a modern AWS data environment.
This role is based on-site in Edmonton. Relocation support is available for the right candidate.
Position Responsibilities

Design, build, and maintain scalable, secure, and performant data pipelines on AWS, with Redshift and Athena at the core of the analytical platform.
Optimize query and warehouse performance on very large datasets (multi-TB tables) through distribution and sort key design, partitioning strategy, file/format optimization, and scan-cost reduction.
Develop robust, production-grade ETL/ELT in Python, with strong attention to testing, error handling, retries, and observability.
Package and deploy data workloads using Docker and containers.
Apply data engineering fundamentals — modeling, data quality, lineage, and reliability — to deliver trustworthy data for analytics and downstream consumers.
Collaborate with stakeholders to translate data needs into well-architected, maintainable solutions.
Set engineering standards and mentor team members, promoting best practices across the AWS data stack (Principal-level scope).
Stay current with the AWS data ecosystem and bring forward improvements in performance, cost, and developer productivity.

Qualifications

Bachelor's degree in Computer Science, Data Engineering, or a related discipline, or equivalent practical experience.
Senior: 5+ years / Principal: 8+ years of hands-on data engineering experience, with significant time spent building on AWS.
Strong production Python for data pipelines and automation.
Demonstrated, in-depth experience with Amazon Redshift and Amazon Athena, including real-world performance and cost optimization.
Proven track record optimizing queries and pipelines on large datasets (multi-terabyte scale) — you can speak to specific before/after wins.
Working experience with Docker / containers as part of your build and deployment workflow.
Solid data engineering fundamentals: data modeling, warehouse/lakehouse design, partitioning, and data quality.
Excellent communication and collaboration skills, with the ability to explain technical trade-offs to varied audiences.

Preferred Qualifications

Experience with AWS CDK (infrastructure as code) and IAM least-privilege design.
Experience with ECS, AWS Step Functions, and AWS Lambda for orchestration and serverless data workloads.
Familiarity with AI-assisted development tools and workflows.
AWS certifications such as AWS Certified Data Engineer – Associate or AWS Certified Solutions Architect.

Benefits

A culture that both wows our customers and employees;
Variety of challenging projects, and the ability to work with leading-edge technologies;
Competitive salary & group benefits;
Generous training and education opportunities;
Diverse team social events;
Be part of a team that believes in diversity, inclusion, and a fun atmosphere!

Lantern is committed to fair and equitable compensation practices. Actual compensation will depend upon an individual's skills, experience, qualifications, location, and other relevant factors. The salary pay range is subject to change and may be modified at any time.